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Record W3105447322 · doi:10.1111/jne.12919

Insulin signalling in hypothalamic neurones

2020· review· en· W3105447322 on OpenAlexafffundabout
Denise D. Belsham, Prasad S. Dalvi

Bibliographic record

VenueJournal of Neuroendocrinology · 2020
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsInsulin resistanceInsulinInsulin receptorEndocrinologyNeuroinflammationNeuroscienceDiabetes mellitusInternal medicineMedicineBiologyDisease

Abstract

fetched live from OpenAlex

Subsequent to the discovery of insulin by Banting and Best in the Department of Physiology at the University of Toronto 100 years ago, the field of insulin signalling and action has grown at a remarkable pace. Yet, the recognition that insulin action in the brain is critical for whole body homeostasis has only recently been appreciated. The hypothalamus is a key region in the brain that responds to circulating insulin by engaging a complex signalling cascade resulting in the ultimate release of neuropeptides that control hunger and feeding. Disruption of this important feedback system can lead to a phenomenon called cellular insulin resistance, where the neurones cease to sense insulin. The factors contributing to insulin resistance, as well as the resulting detrimental effects, include the induction of neuroinflammation, endoplasmic reticulum stress and alterations in the architecture of the blood-brain barrier that allow transport of insulin into the brain. These manifestations usually change energy balance, causing weight gain, often resulting in obesity and its deadly comorbidities, including type 2 diabetes mellitus, cardiovascular disease and metabolic syndrome. Nonetheless, there is still hope because the signal transduction pathways can be targeted at a number of levels by neurone-specific therapeutics. With the advent of unique cell models for investigating the mechanisms involved in these processes, the discovery of novel targets is increasingly possible. Although we are still looking for a cure for diabetes, Banting and Best would be impressed at how far their discovery has advanced and the contemporary knowledge that has been accumulated based on insulin action.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.089
GPT teacher head0.328
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2020
Admission routes3
Has abstractyes

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